MicroRNAs (miRNAs) are non-coding small RNAs that play roles in regulating gene expression. Some miRNAs have been classed as epigenetic regulators of metabolism and energy homeostasis. Previous reports indicated that the miRNAs miR-27a and miR-143 were involved in lipid metabolism in human and rodents. To determine the roles of porcine miR-27a and miR-143 in adipocyte lipid metabolism, porcine adipocytes were cultured and allowed to induce differentiation for 10 days. The lipid-filled adipocytes were then transfected with miRNA mimics and inhibitors. We measured how the indicators of adipogenesis and adipolysis in porcine adipocytes were affected by the over-expression and by the inhibition of both miR-27a and miR-143. The results indicated that the over-expression of miR-27a could accelerate adipolysis releasing significantly more glycerol and free fatty acids than the negative control (P < 0.001), while the mimic of miR-143 expression, promoted adipogenesis by accumulating more triglycerides (P < 0.001) in the adipocytes. In addition, we demonstrated that there was good correlation (r > 0.98, P < 0.001) between the indicators of adipolysis in cell lysates and in the culture medium.
Patient stratification has been studied widely to tackle subtype diagnosis problems for effective treatment. Due to the dimensionality curse and poor interpretability of data, there is always a long-lasting challenge in constructing a stratification model with high diagnostic ability and good generalization. To address these problems, this paper proposes two novel evolutionary multiobjective clustering algorithms with ensemble (NSGA-II-ECFE and MOEA/D-ECFE) with four cluster validity indices used as the objective functions. First, an effective ensemble construction method is developed to enrich the ensemble diversity. After that, an ensemble clustering fitness evaluation (ECFE) method is proposed to evaluate the ensembles by measuring the consensus clustering under those four objective functions. To generate the consensus clustering, ECFE exploits the hybrid co-association matrix from the ensembles and then dynamically selects the suitable clustering algorithm on that matrix. Multiple experiments have been conducted to demonstrate the effectiveness of the proposed algorithm in comparison with seven clustering algorithms, twelve ensemble clustering approaches, and two multiobjective clustering algorithms on 55 synthetic datasets and 35 real patient stratification datasets. The experimental results demonstrate the competitive edges of the proposed algorithms over those compared methods. Furthermore, the proposed algorithm is applied to extend its advantages by identifying cancer subtypes from five cancer-related single-cell RNA-seq datasets.
Compared to normal aging adults, individuals with amnestic mild cognitive impairment (aMCI) have significantly increased risk for progressing into Alzheimer’s disease (AD). Autopsy studies found that most of the brains of aMCI cases showed anatomical features associated with AD pathology. The recent development of non-invasive neuroimaging technique, such as diffusion tensor imaging (DTI), makes it possible to investigate the microstructures of the cerebral white matter in vivo. We hypothesized that disrupted white matter (WM) integrity existed in aMCI. So we used DTI technique, by measuring fractional anisotropy (FA) and mean diffusivity (MD), to test the brain structures involved in patients with aMCI. DTI scans were collected from 40 patients with aMCI, and 28 normal controls (NC). Tract-based spatial statistics (TBSS) analyses of whole-brain FA and MD images in each individual and group comparisons were carried out. Compared to NC, aMCI patients showed significant FA reduction bilaterally, in the association and projection fibers of frontal, parietal, and temporal lobes, corpus callosum, bilateral corona radiation, right posterior thalamic radiation and right sagittal stratum. aMCI patients also showed significantly increased MD widespreadly in the association and projection fibers of frontal, parietal and temporal lobes, and corpus callosum. Assessment of the WM integrity of the frontal, parietal, temporal lobes, and corpus callosum by using DTI measures may aid early diagnosis of aMCI.
Functional differences in the different types of adipose tissue and the impact of their dysfunction on metabolism are associated with the regional distribution of adipose depots. Here we show a genome-wide comparison between the transcriptomes of one source of subcutaneous and two sources of visceral adipose tissue in the pig using an RNA-seq approach. We obtained ~32.3 million unique mapped reads which covered ~80.2% of the current annotated transcripts across these three sources of adipose tissue. We identified various genes differentially expressed between subcutaneous and visceral adipose tissue, which are potentially associated with the inflammatory features of visceral adipose tissue. These results are of benefit for understanding the phenotypic, metabolic and functional differences between different types of adipose tissue that are deposited in different body sites.
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